Data Item Query Management

PURPOSE The essence of guideline recommendations often is intertwined in large texts. This impedes clinical implementation and evaluation and delays timely modular revisions needed to deal with an ever-growing amount of knowledge and application of personalized medicine. The aim of this project was to model guideline recommendations as data-driven clinical decision trees (CDTs) that are clinically interpretable and suitable for implementation in decision support systems. METHODS All recommendations of the Dutch national breast cancer guideline for nonmetastatic breast cancer were translated into CDTs. CDTs were constructed by nodes, branches, and leaves that represent data items (patient and tumor characteristics [eg, T stage]), data item values (eg, T2 or less), and recommendations (eg, chemotherapy), respectively. For all data items, source of origin was identified (eg, pathology), and where applicable, data item values were defined on the basis of existing classification and coding systems (eg, TNM, Breast Imaging Reporting and Data System, Systematized Nomenclature of Medicine). All unique routes through all CDTs were counted to measure the degree of data-based personalization of recommendations. RESULTS In total, 60 CDTs were necessary to cover the whole guideline and were driven by 114 data items. Data items originated from pathology (49%), radiology (27%), clinical (12%), and multidisciplinary team (12%) reports. Of all data items, 101 (89%) could be classified by existing classification and coding systems. All 60 CDTs could be integrated in an interactive decision support app that contained 376 unique patient subpopulations. CONCLUSION By defining data items unambiguously and unequivocally and coding them to an international coding system, it was possible to present a complex guideline as systematically constructed modular data-driven CDTs that are clinically interpretable and accessible in a decision support app.

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BANDWIDTH ALLOCATION IN A WIRELESS BROADCAST SYSTEM

International Journal of Information Technology & Decision Making ◽

10.1142/s0219622003000847 ◽

2003 ◽

Vol 02 (04) ◽

pp. 629-640 ◽

Cited By ~ 2

Author(s):

ASLIHAN CELIK ◽

STEVE NAHMIAS ◽

RHONDA RIGHTER

Keyword(s):

Bandwidth Allocation ◽

Optimal Allocation ◽

Data Item ◽

Wireless Broadcast ◽

The Individual

We develop a model for broadcasting data to wireless appliances. Any data item may either be "pushed", or broadcast without waiting for requests for the item, or it may be "pulled", or broadcast in response to a request. Pushing items is cheaper than handling the individual requests, but if pushed items are not wanted, the bandwidth for broadcasting them is wasted. We determine the optimal allocation of bandwidth between pushed and pulled items.

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